Stochastic Reconfiguration and Optimal Coordination of V2G Plug-in Electric Vehicles Considering Correlated Wind Power Generation

被引:152
|
作者
Kavousi-Fard, Abdollah [1 ]
Niknam, Taher [1 ]
Fotuhi-Firuzabad, Mahmud [2 ]
机构
[1] Shiraz Univ Technol SUTech, Dept Elect & Elect Engn, Shiraz 7188975369, Iran
[2] Sharif Univ Technol, Dept Elect Engn, Tehran 113659363, Iran
关键词
Distribution feeder reconfiguration (DFR); plug-in electric vehicle (PEV); unscented transformation (UT); vehicle-to-grid (V2G); DISTRIBUTION FEEDER RECONFIGURATION; LOAD; UNCERTAINTY; NETWORKS; DEMAND; IMPACT;
D O I
10.1109/TSTE.2015.2409814
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper investigates the optimal operation of distribution feeder reconfiguration (DFR) strategy in the smart grids with high penetration of plug-in electric vehicles (PEVs) and correlated wind power generation. The increased utilization of PEVs in the system with stochastic volatile behavior along with the high penetration of renewable power sources such as wind turbines (WTs) can create new challenges in the system that will affect the DFR strategy greatly. In order to reach the most efficiency from the PEVs, the idea of vehicle-to-grid (V2G) is employed in this paper to make a bidirectional power flow (either charging/discharging or idle mode) strategy when providing the main charging needs of PEVs. In this regard, we suggest a new stochastic framework based on unscented transformation (UT) to model the uncertainties of the PEVs' behaviors when considering the correlated power generation of WTs. The feasibility and satisfying performance of the proposed framework are examined on the IEEE 69-bus test system.
引用
收藏
页码:822 / 830
页数:9
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